The present invention relates to digital communications, and more particularly to channel estimators and equalization methods utilized in digital communications.
In recent years, digital wireless communication systems have been used to convey a variety of information between multiple locations. With digital communications, information is translated into a digital or binary form, referred to as bits, for communications purposes. The transmitter maps this bit stream into a modulated symbol stream, which is detected at the digital receiver and mapped back into bits and information.
In digital wireless communications, the radio environment presents many difficulties that impede successful communications, for example, those caused by the many signal paths traversed by radio signals before arriving at a receiver. One difficulty occurs when the multiple signal paths are much different in length. In this case, time dispersion occurs, in which multiple signal images arrive at the receiver antenna at different times, giving rise to signal echoes. This causes inter-symbol interference (ISI), a phenomenon in which the echoes of one symbol interfere with subsequent symbols.
Time dispersion can be mitigated by using an equalizer. Common forms of equalization are provided by linear equalizers, decision-feedback equalizers, and maximum-likelihood sequence-estimation (MLSE) equalizers. A linear equalizer tries to undo the effects of the channel by filtering the received signal. A decision-feedback equalizer exploits previous symbol detections to cancel out the inter-symbol interference from echoes of these previous symbols. Finally, an MLSE equalizer hypothesizes various transmitted symbol sequences and, with a model of the dispersive channel, determines which hypothesis best fits the received data. These equalization techniques are well known to those skilled in the art, and can be found in standard textbooks such as J. G. Proakis, Digital Communications, 2nd ed., New York: McGraw-Hill, 1989. Equalizers are commonly used in TDMA systems, such as D-AMPS and GSM.
Of the three common equalization techniques, MLSE equalization is preferable from the point of view of performance accuracy. In the MLSE equalizer, all possible transmitted symbol sequences are considered. For each hypothetical sequence, the received signal samples are predicted using a model of the multipath channel. The difference between the predicted received signal samples and the actual received signal samples, referred to as the prediction error, gives an indication of how good a particular hypothesis is. The squared magnitude of the prediction error is used as a metric to evaluate a particular hypothesis. This metric is accumulated for different hypotheses for use in determining which hypotheses are better. This process is efficiently realized using the Viterbi algorithm, which is a form of dynamic programming.
However, under certain operating conditions, signals arriving at a receiver may not create significant levels of inter-symbol interference. When ISI is insignificant, or absent, the equalizer actually adds more noise to the detection statistic than it removes, particularly when the channel varies rapidly. Under these conditions, it would be desirable to switch the equalizer off in favor of another detection device, e.g., a differential detector, which may perform better under non-time dispersive conditions. Moreover, an equalizer is relatively complex computationally compared with a differential detector. Thus, periodically switching off the equalizer in favor of a differential detector would save MIPS which, in turn, would reduce battery consumption.
As another example, in direct sequence CDMA systems, RAKE receivers are commonly employed. However, if too many RAKE taps are employed, performance degrades.
Accordingly, it would be desirable to provide a receiver in which an appropriate detection technique could be dynamically identified and implemented, e.g., a detector which uses an appropriate number of channel taps.
FIG. 1 depicts a conventional channel estimator and channel equalizer for use in a burst transmission system such as, for example, the GSM system. Conventional apparatuses of the type illustrated in FIG. 1 are well-known, and are described in standard textbooks such as the above-referenced one by Proakis. A received signal 101 with predefined burst length is stored in a memory 103. A portion of the received burst that includes a received training signal is supplied by the memory 103 to a channel estimator 104. The K:th order (K fixed) channel filter taps {hi}i=1,K are computed from the received signal while referring to an input training signal 102. The channel filter taps are then fed to an equalizer 105 having a fixed number of states, MKxe2x88x921 where M is the number of possible symbols. The equalizer 105 may be any of a number of types of equalizer, including a Viterbi equalizer. The output of the equalizer 105 is the decided symbol 106.
U.S. Pat. No. 5,644,603, which issued on Jul. 1, 1997 to Ushirokawa, describes a channel estimator and channel equalizer having a variable number of states. This is illustrated in FIG. 2. A received signal 201 with a predefined burst length is stored in a memory 203. A portion of the received burst that includes a received training signal is supplied by the memory 203 to a channel estimator 204. The K:th order (K fixed) channel filter taps {hi}i=1,K are computed from the received signal while referring to an input training signal 202. The channel filter taps are then fed into a control unit 206 that identifies the last one of the filter taps that has a larger power than a predetermined threshold power level. The power in those filter taps that lie beyond the last identified filter tap can be assumed to be zero. When it is decided that the latest response is the L:th response (Lxe2x89xa6K), the filter taps {hi}L=1,L are fed to a Viterbi equalizer 205 having MLxe2x88x921 states. The output of the Viterbi equalizer 205 is the decided symbol 207.
As explained in the above-referenced U.S. Pat. No. 5,644,603, a primary reason for reducing the number of states is to reduce the average amount of required processing. A reduction in processing load translates into a reduction in power consumption. International patent publication WO 96/13910 explains that a reduction in the small channel filter taps can also result in a better model of the true radio channel.
The foregoing and other objects are achieved in channel estimation methods and apparatuses for use in a radio receiver. In accordance with one aspect of the invention, channel estimation comprises receiving a received training sequence portion of a radio signal; and estimating a plurality of channel model structures based on the received training sequence and a predetermined training sequence, wherein, for each of the plurality of channel model structures, corresponding coefficients are determined by using all of a set of one or more taps associated with the corresponding channel model structure and no others.
In another aspect of the invention, at least one of the plurality of channel model structures is a channel model structure of order K, and having fewer than K coefficients.
In yet another aspect of the invention, channel estimation further comprises filtering a non-filtered training sequence to generate the predetermined training sequence, wherein the filtering is substantially the same as known filtering to which a transmitted training sequence has been subjected.
In still another aspect of the invention, channel estimation further comprises generating, for each of the plurality of channel model structures, a variance measure representing an amount of variance between an estimated value generated by the channel model structure and a received signal value.
In yet another aspect of the invention, channel estimation further comprises selecting an optimum channel model structure from the plurality of channel model structures, based on the variance measures.
In still another aspect of the invention, selection of an optimum channel model is performed by using the variance measures in an Akaike Information Criteria test.
In yet another aspect of the invention, channel estimation further comprises generating a number of states associated with the optimum channel model structure; and supplying the optimum channel model structure and the number of states to an equalizer. The equalizer may then generate a decided signal from a received radio signal, the optimum channel model structure and the number of states.